Federated learning (FL) has emerged as a popular machine learning paradigm which allows multiple data owners to train models collaboratively with out sharing their raw datasets. It holds potential for ...
Machine learning-based neural network potentials often cannot describe long-range interactions. Here the authors present an approach for building neural network potentials that can describe the ...
A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
Researchers examining the brain at a single-neuron level found that computation happens not just in the interaction between neurons, but within each individual neuron. Each of these cells, it turns ...
A Cornell research group led by Prof. Peter McMahon, applied and engineering physics,has successfully trained various physical systems to perform machine learning computations in the same way as a ...
SANTA CLARA, Calif.--(BUSINESS WIRE)-- What’s New: Today, Intel and the National Science Foundation (NSF) announced award recipients of joint funding for research into the development of future ...
Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Google’s Cloud Tensor Processing Units are ...
A major challenge to developing better neural prostheses is sensory encoding: transforming information captured from the environment by sensors into neural signals that can be interpreted by the ...
SANTA CLARA, Calif.--(BUSINESS WIRE)--What’s New: Today, Intel and the National Science Foundation (NSF) announced award recipients of joint funding for research into the development of future ...
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